846 resultados para optimal robots


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Implementation and collapse of exchange rate pegging schemes are recur- rent events. A currency crisis (pegging) is usually followed by an economic downturn (boom). This essay explains why a benevolent government should pursue Þscal and monetary policies that lead to those recurrent currency crises and subsequent periods of pegging. It is shown that the optimal policy induces a competitive equilibrium that displays a boom in periods of below average de- valuation and a recession in periods of above average devaluation. A currency crisis (pegging) can be understood as an optimal policy answer to a recession (boom).

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We characterize optimal policy in a two-sector growth model with xed coeÆcients and with no discounting. The model is a specialization to a single type of machine of a general vintage capital model originally formulated by Robinson, Solow and Srinivasan, and its simplicity is not mirrored in its rich dynamics, and which seem to have been missed in earlier work. Our results are obtained by viewing the model as a specific instance of the general theory of resource allocation as initiated originally by Ramsey and von Neumann and brought to completion by McKenzie. In addition to the more recent literature on chaotic dynamics, we relate our results to the older literature on optimal growth with one state variable: speci cally, to the one-sector setting of Ramsey, Cass and Koopmans, as well as to the two-sector setting of Srinivasan and Uzawa. The analysis is purely geometric, and from a methodological point of view, our work can be seen as an argument, at least in part, for the rehabilitation of geometric methods as an engine of analysis.

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This paper discusses ~he widespread inefficiency in water pricing today and uses the State of California as an example. After solving the Planner' s Problem I conclude that water for irrigation should cost more than for domestic use. The optimal price leveI can be calculated from a correct measure of the true marginal cost of supply.

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This paper investigates the importance of the fiow of funds as an implicit incetive provided by investors to portfolio managers in a two-period relationship. We show that the fiow of funds is a powerful incentive in an asset management contract. We build a binomial moral hazard model to explain the main trade-ofIs in the relationship between fiow, fees and performance. The main assumption is that efIort depend" on the combination of implicit and explicit incentives while the probability distrioutioll function of returns depends on efIort. In the case of full commitment, the investor's relevant trade-ofI is to give up expected return in the second period vis-à-vis to induce efIort in the first período The more concerned the investor is with today's payoff. the more willing he will be to give up expected return in the following periods. That is. in the second period, the investor penalizes observed low returns by withdrawing resources from non-performing portfolio managers. Besides, he pays performance fee when the observed excess return is positive. When commitment is not a plausible hypothesis, we consider that the investor also learns some symmetríc and imperfect information about the ability of the manager to generate positive excess returno In this case, observed returns reveal ability as well as efIort choices exerted by the portfolio manager. We show that implicit incentives can explain the fiow-performance relationship and, conversely, endogenous expected return determines incentives provision and define their optimal leveIs. We provide a numerical solution in Matlab that characterize these results.

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This paper considers two-sided tests for the parameter of an endogenous variable in an instrumental variable (IV) model with heteroskedastic and autocorrelated errors. We develop the nite-sample theory of weighted-average power (WAP) tests with normal errors and a known long-run variance. We introduce two weights which are invariant to orthogonal transformations of the instruments; e.g., changing the order in which the instruments appear. While tests using the MM1 weight can be severely biased, optimal tests based on the MM2 weight are naturally two-sided when errors are homoskedastic. We propose two boundary conditions that yield two-sided tests whether errors are homoskedastic or not. The locally unbiased (LU) condition is related to the power around the null hypothesis and is a weaker requirement than unbiasedness. The strongly unbiased (SU) condition is more restrictive than LU, but the associated WAP tests are easier to implement. Several tests are SU in nite samples or asymptotically, including tests robust to weak IV (such as the Anderson-Rubin, score, conditional quasi-likelihood ratio, and I. Andrews' (2015) PI-CLC tests) and two-sided tests which are optimal when the sample size is large and instruments are strong. We refer to the WAP-SU tests based on our weights as MM1-SU and MM2-SU tests. Dropping the restrictive assumptions of normality and known variance, the theory is shown to remain valid at the cost of asymptotic approximations. The MM2-SU test is optimal under the strong IV asymptotics, and outperforms other existing tests under the weak IV asymptotics.

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This work analyzes the optimal design of an unemployment insurance program for couples, whose joint search problem in the labor market differ significantly from the problem faced by single agents. We use a version of the sequential search model of the labor market adapted to married agents to compare optimal constant policies for single and married agents, as well as characterize the optimal constant policy when the agency faces single and married agents simultaneously. Our main result is that an agency that gives equal weights to single and married agents will want to give equal utility promises to both types of agents and spend more on the single agent.

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This work aims to analyze the interaction and the effects of administered prices in the economy, through a DSGE model and the derivation of optimal monetary policies. The model used is a standard New Keynesian DSGE model of a closed economy with two sectors companies. In the first sector, free prices, there is a continuum of firms, and in the second sector of administered prices, there is a single firm. In addition, the model has positive trend inflation in the steady state. The model results suggest that price movements in any sector will impact on both sectors, for two reasons. Firstly, the price dispersion causes productivity to be lower. As the dispersion of prices is a change in the relative price of any sector, relative to general prices in the economy, when a movement in the price of a sector is not followed by another, their relative weights will change, leading to an impact on productivity in both sectors. Second, the path followed by the administered price sector is considered in future inflation expectations, which is used by companies in the free sector to adjust its optimal price. When this path leads to an expectation of higher inflation, the free sector companies will choose a higher mark-up to accommodate this expectation, thus leading to higher inflation trend when there is imperfect competition in the free sector. Finally, the analysis of optimal policies proved inconclusive, certainly indicating that there is influence of the adjustment model of administered prices in the definition of optimal monetary policy, but a quantitative study is needed to define the degree of impact.

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We study optimal labor income taxation in non-competitive labor markets. Firms offer screening contracts to workers who have private information about their productivity. A planner endowed with a Paretian social welfare function tries to induce allocations that maximize its objective. We provide necessary and sufficient conditions for implementation of constrained efficient allocations using tax schedules. All allocations that are implementable by a tax schedule display negative marginal tax rates for almost all workers. Not all allocations that are implementable in a competitive setting are implementable in this noncompetitive environment.

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We discuss a general approach to building non-asymptotic confidence bounds for stochastic optimization problems. Our principal contribution is the observation that a Sample Average Approximation of a problem supplies upper and lower bounds for the optimal value of the problem which are essentially better than the quality of the corresponding optimal solutions. At the same time, such bounds are more reliable than “standard” confidence bounds obtained through the asymptotic approach. We also discuss bounding the optimal value of MinMax Stochastic Optimization and stochastically constrained problems. We conclude with a small simulation study illustrating the numerical behavior of the proposed bounds.

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My dissertation focuses on dynamic aspects of coordination processes such as reversibility of early actions, option to delay decisions, and learning of the environment from the observation of other people’s actions. This study proposes the use of tractable dynamic global games where players privately and passively learn about their actions’ true payoffs and are able to adjust early investment decisions to the arrival of new information to investigate the consequences of the presence of liquidity shocks to the performance of a Tobin tax as a policy intended to foster coordination success (chapter 1), and the adequacy of the use of a Tobin tax in order to reduce an economy’s vulnerability to sudden stops (chapter 2). Then, it analyzes players’ incentive to acquire costly information in a sequential decision setting (chapter 3). In chapter 1, a continuum of foreign agents decide whether to enter or not in an investment project. A fraction λ of them are hit by liquidity restrictions in a second period and are forced to withdraw early investment or precluded from investing in the interim period, depending on the actions they chose in the first period. Players not affected by the liquidity shock are able to revise early decisions. Coordination success is increasing in the aggregate investment and decreasing in the aggregate volume of capital exit. Without liquidity shocks, aggregate investment is (in a pivotal contingency) invariant to frictions like a tax on short term capitals. In this case, a Tobin tax always increases success incidence. In the presence of liquidity shocks, this invariance result no longer holds in equilibrium. A Tobin tax becomes harmful to aggregate investment, which may reduces success incidence if the economy does not benefit enough from avoiding capital reversals. It is shown that the Tobin tax that maximizes the ex-ante probability of successfully coordinated investment is decreasing in the liquidity shock. Chapter 2 studies the effects of a Tobin tax in the same setting of the global game model proposed in chapter 1, with the exception that the liquidity shock is considered stochastic, i.e, there is also aggregate uncertainty about the extension of the liquidity restrictions. It identifies conditions under which, in the unique equilibrium of the model with low probability of liquidity shocks but large dry-ups, a Tobin tax is welfare improving, helping agents to coordinate on the good outcome. The model provides a rationale for a Tobin tax on economies that are prone to sudden stops. The optimal Tobin tax tends to be larger when capital reversals are more harmful and when the fraction of agents hit by liquidity shocks is smaller. Chapter 3 focuses on information acquisition in a sequential decision game with payoff complementar- ity and information externality. When information is cheap relatively to players’ incentive to coordinate actions, only the first player chooses to process information; the second player learns about the true payoff distribution from the observation of the first player’s decision and follows her action. Miscoordination requires that both players privately precess information, which tends to happen when it is expensive and the prior knowledge about the distribution of the payoffs has a large variance.

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Desde há alguns anos que vêm sendo desenvolvidas, em vários sítios do mundo, experiências com a utilização de Robots como uma ferramenta educativa, com especial incidência ao nível do Ensino Superior e em alguns casos no Ensino Básico ou Secundário. Neste trabalho de investigação pretende-se fazer uma análise crítica sobre o uso dos robots no ensino da programação nas disciplinas de Informática do Ensino Secundário e disciplina de Inteligência Artificial da Licenciatura do Curso de Engenharia Informática. Com o objectivo de usar o robot como mediador entre o aluno e o ensino da programação, identificamos os conteúdos programáticos das diversas disciplinas do Ensino Secundário e fizemos o levantamento de ferramentas e soluções tecnológicas existentes que pudessem ser aplicadas nas aulas. Como contributo desta investigação pretende-se: (i)disponibilizar uma série de problemas adequados aos vários conteúdos programáticos, para serem utilizados nas salas de aulas; (ii) criar e optimizar ferramentas, mais concretamente plataformas de programação, para os alunos resolverem os problemas através dos robots.

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A Escola e o Ensino, através da evolução dos diferentes sistemas que os caracterizaram ao longo dos tempos, tiveram e têm por objectivo não só a transmissão de conhecimentos mas também a preparação dos cidadãos mais jovens para a sua integração na vida social da sua comunidade. A escola atravessa momentos difíceis e os papéis dos intervenientes são questionados diariamente. Tal tem dado origem a alterações e a mudanças na concepção organizacional, de estratégia e de objectivos da escola e do próprio ensino. A profissão docente deixou de ser uma mera transmissão de saber, exigindo-se muito mais ao professor. O seu papel inclui já novas questões, tais como, como ensinar?, como fazer aprender? e como motivar os outros para que queiram aprender? A evolução tecnológica e a sua integração no ensino têm sido das principais fontes para a alteração operada sobre a escola e o seu objectivo. O desenvolvimento das tecnologias de informação e de comunicação (TIC) têm vindo a proporcionar novas formas de comunicar e de transmitir informação. A habilitação profissional para a docência no ensino básico e secundário implica a Prática de Ensino Supervisionado. Para além das planificações e da implementação das metodologias adoptadas visando o processo de ensino-aprendizagem da Matemática ao nível do 10º ano de escolaridade, desenvolvemos um projecto de cariz qualitativo cujo objectivo seria a análise da aplicabilidade da robótica, na sala de aula, enquanto elemento mediador e potenciador do processo de aprendizagem no tema das funções. A revisão bibliográfica demonstra que a robótica tem merecido elogios enquanto factor motivador e elemento que faculta uma conexão entre diversas representações, nomeadamente, os conceitos teóricos e a praticabilidade. O desenvolvimento de diversas actividades com duas turmas do 10º ano de escolaridade, utilizando robots LEGO Minstorms, revelou que a robótica não só é um elemento mediador do processo ensino-aprendizagem mas também, e sobretudo, é um catalisador da motivação, cooperação e envolvência dos alunos, levando-os, numa perspectiva construcionista, a construir conhecimento e a concretizar o simbolismo abstracto presente na Matemática.

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Nowadays, the development of intelligent agents intends to be more refined, using improved architectures and reasoning mechanisms. Revise the beliefs of an agent is also an important subject, due to the consistency that agents should have about their knowledge. In this work we propose deliberative and argumentative agents using Lego Mindstorms robots, Argumentative NXT BDI-like Agents. These agents are built using the notions of the BDI model and they are capable to reason using the DeLP formalism. They update their knowledge base with their perceptions and revise it when necessary. Two variations are presented: the Single Argumentative NXT BDI-like Agent and the MAS Argumentative NXT BDI-like Agent.

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Nesta dissertação começo por fazer uma pequena reflexão sobre a minha experiência profissional. Seguindo-se a abordagem teórica que esteve como suporte para o desenvolvimento do meu estudo de caso, implementado nas minhas quatro turmas de 7º ano, num total de 109 alunos. Este estudo, baseou-se na aplicação de duas tarefas na unidade temática das Funções utilizando as tecnologias, nomeadamente, do robot MINDSTORMS® NXT da LEGO® e do software de geometria dinâmica GeoGebra como ferramentas de introdução e consolidação de conteúdos. O propósito desta tese de mestrado centra-se na importância e na relevância da utilização destas tecnologias no ensino da Matemática, no caso específico das Funções no 7º ano. A recolha e análise dos dados para a elaboração desta tese foram baseadas exclusivamente na vivência dos alunos aquando da realização das tarefas propostas, através da grelha de observação diária, da gravação em áudio e vídeo, de fotografias, das fichas de trabalho e dos questionários, visto ter optado por uma investigação qualitativa em que a participação dos intervenientes é fundamental. Foi evidente uma aceitação positiva por parte dos alunos a estas tecnologias. Assim sendo, permitiu-me concluir que realmente a aprendizagem dos mesmos foi significativa visto que a utilização destas ferramentas facilitou a aprendizagem de alguns conceitos abordados na unidade temática das Funções.